Adapting to Technological Change: Cognitive and Emotional Response of Older Employees in the Industrial Sector

As automation and artificial intelligence (AI) continue to transform industrial processes, older employees often face challenges in adapting, mainly due to limited digital skills, increased cognitive demands, and psychological resistance. This study examines how employees over 50 adapt to digital transformation in two energy companies. One hundred employees participated in a three-month study, split into two groups: one received standard training, while the other underwent age-adapted training. Data collection involved LMS tracking, knowledge testing, forum analysis, surveys, and the Perceived Stress Scale (PSS).Results showed that the age-adapted group had higher knowledge retention (88% vs. 72%), lower stress levels (3.2 vs. 6.5), more engagement, and greater satisfaction with the learning process. They also demonstrated better confidence and smoother adaptation to automation tools. However, a follow-up after one year revealed a decline in long-term learning motivation. Around 30% of participants were reluctant to continue training, citing fatigue and interference with their primary work duties.The findings highlight the need for tailored training programs and psychological support for older workers. Age-sensitive strategies reduce stress, increase engagement, and improve knowledge retention, offering insights for inclusive automation strategies in age-diverse workforces.